American Express is one of the world’s largest payment services provider. It is a Day 1 company and one of the most coveted in Analytics profile during the insti placement process. Akash Garg, a Dual Degree Civil Engineering alumnus of 2018, speaks to Chennai36 about his placement experience with AmEx.
1. How did you get interested in analytics and how did you zero in on AmEx?
Till the end of my 3rd year, I was not really sure about what I was interested in, although I figured I would eventually take a job in a core company related to my branch. But this idea came crashing down when I saw my B.Tech batchmates who were sitting for placements in their 4th year get placed in relatively low paying jobs at core companies. What I witnessed (bad core placements), really made me reconsider my options. Hence, I decided to try out analytics and I got hooked to it. Well, as to why AmEx, I’m kind of an exception! But also AmEx is a world leader in leveraging Machine Learning for credit risk modeling – which was the domain I was interested in.
2. How were you an outlier to the conventional AmEx placement process?
AmEx conducts this data analytics competition called ‘Analyze this’. So in my 4th year, I was the national winner of that competition, which entitles me for a PPI – Pre Placement Interview.
3. How did you prepare for the competition?
As I mentioned above, after the 4th-year winter, my affinity for core weaned away after seeing my batchmates’ placements. Hence, that year I decided to take a lot of Data Science related courses in insti. Once I was confident enough of my skills, I got my hands dirty by participating in Data science competitions, especially on Analytics. I focussed more on solving problems rather than just theoretical knowledge. So during the semester, as part of Tech-Soc, a Big-Data challenge was conducted which I won. It really boosted my confidence and I started taking Data Science a bit more seriously. I started reading more about Machine Learning and the analytics world religiously. It was in my final year when I won ‘AmEx’s Analyse This’ competition. In the lead-up to the competition, I was convinced, that cracking this was my only way to get placed in AmEx owing to my not so good CG since AmEx shortlisted students with 8 or plus CG. The competition was in August and was for a week, my friend (branch mate) and I spent close to 8 days solving only the given problem statement and in the process did not attend any classes. After the hard work and toil, we were declared as winners. Winning the competition was a turning point in my career since it also gave me enough confidence to crack and win a few other coveted competitions.
4. Tell us more about your Personal interview?
I had two rounds of interview – one was with a Senior Manager and the other was with the VP. Both were technical in nature. The manager’s interview was on machine learning algorithms that I mentioned in my resume, my internship and the puzzles. Since the manager already knew that I had won the competition, she asked me about my performances in other data science hackathons where I had participated. Also my DDP – Dual Degree Project was about Machine Learning Applications in Civil Engineering, which caught her interest. In the second round with the VP, he started the interview by asking me to describe myself. For this question, I answered by listing out my technical achievements when he stopped and asked me to tell more about my family background, hobbies, favorite time-pass, etc.
5. What were the internships you did and do you think it played a role in your placement process?
In my 3rd year summer, I did a core intern through the institute portal. During the later part of my 4th year, I invested a lot of time learning the nuts and bolts of Data Science. And hence in my 4th-year summer, I interned with IFMR Capital in Research Park. It was about financial risk modeling of the firm’s retail loan lending portfolio. This internship gave me a broader perspective of Machine Learning applications in solving real-world problems. I loved the work and decided to pursue Data Science as my career option. It also helped me narrow down the subdomain that I wanted to pursue, which is the intersection of Machine Learning coupled with financial data having real-world implications.
6. How important are PoRs, CGPA, and extracurricular activities for the shortlist and during the placement interview?
Since I won the competition, there were no CG criteria for the winners. But if you are applying through the insti portal then there was a CG cutoff of around 8 during my time. PoRs are not really significant for AmEx. Only projects related to Machine Learning or Data Science Internships/ Competitions are enquired about.
7. What is your current role at AmEx?
AmEx has two locations, I’m working in Gurgaon which manages the business aspect of the company while it has an office in Bangalore which is more tech and software oriented. I am currently a part of the Model Risk management group which reviews the correctness of the model developed by the modeling team for its intended use by examining the model data, assumptions, analysis, calculations and results. In simpler terms, it is responsible for the independent oversight of models across the company and keeps a check on whether the modeling team has developed a technically sound model before it is deployed for business use. Since I am interested in ML research as well, that specific arm of the company has given me side-task of identifying areas where AmEx is yet to break into the ML world using data the company has.
8. What advice would you give to the current set of students aspiring for a data analyst role at AmEx?
Even though I had won the competition which made things easier for me during the placement process, junta who are going through the insti placement process must prepare very well for the initial test conducted by AmEx. Two key factors in those tests are speed and accuracy. As the test is relatively easy, most of the candidates who get shortlisted might have scored almost full marks in the test, so here timing comes into play, which can decide your shortlist. Your resume must contain some projects or interns related to ML or DS. Since they follow a points-based system wherein they allocate points for your resume and your performance in the tests, having ML/DS related experience will add more to the overall score.
Also, participate in data hackathons and compete as much as you can, they help you improve data science skills. I wouldn’t recommend doing many insti courses or MOOCs since I have seen many of my own batchmates do 7-8 courses and yet when it comes to the practical knowledge they seem to lag behind. The recruiter also cares more about your performance in competitions rather than the number of courses you did online.
Author: Pranav Hari (DD-CE ’22)